The biochemical composition of a cell is a complex mix of biological molecules including, but not limited to, proteins, nucleic acids, lipids, and carbohydrates. The composition and interaction of the biological molecules determines the metabolic state of a cell. The metabolic state of the cell will dictate the type of cell and its function (i.e., red blood cell, epithelial cell, etc.). Tissue is generally understood to mean a group of cells that work together to perform a function. Raman spectroscopic techniques provide information about the biological molecules contained in cells and tissues and therefore provide information about the metabolic state. As the cell's or tissue's metabolic state changes from the normal state to a diseased state, Raman spectroscopic techniques can provide information to indicate the metabolic change and therefore serve to diagnose and predict the outcome of a disease. Cancer is a prevalent disease, so physicians are very concerned with being able to accurately diagnose cancer and to determine the best course of treatment.
Raman spectroscopy may be explored for detection of various types of diseases in particular cancers. Because Raman spectroscopy is based on irradiation of a sample and detection of scattered radiation, it can be employed non-invasively to analyze biological samples in situ. Thus, little or no sample preparation is required. Raman spectroscopy techniques can be readily performed in aqueous environments because water exhibits very little, but predictable, Raman scattering. It is particularly amenable to in vivo measurements as the powers and excitation wavelengths used are non-destructive to the tissue and have a relatively large penetration depth.
Raman Molecular Imaging (RMI) is a reagentless tissue imaging approach based on the scattering of laser light from tissue samples. The approach yields an image of a sample wherein each pixel of the image is the Raman spectrum of the sample at the corresponding location. The  Raman spectrum carries information about the local chemical environment of the sample at each location. RMI has a spatial resolving power of approximately 250 nm and can potentially provide qualitative and quantitative image information based on molecular composition and morphology.
The vast majority of diseases, in particular cancer cases, are pathologically diagnosed using tissue from a biopsy specimen. An experienced pathologist can provide diagnostic information used to make management decisions for the treatment of the cancer. In the case of renal disease, the diagnosis of renal oncocytoma (OC) and chromophobe renal cell carcinoma (ChRCC) based on histological features can often be challenging. Currently, there are no reliable immunohistochemical markers which separate these two neoplasms. Because OC is benign and ChRCC may behave aggressively, the correct identification of these diseases is crucial. A reliable method for distinguishing between OC and ChRCC may assist clinicians to improve prognoses and treatment options for patients with kidney disease.
Therefore it is desirable to devise methodologies that use Raman spectroscopy techniques to differentiate various cell types (e.g., normal, malignant, benign, etc.), to classify biological samples under investigation (e.g., a normal tissue, a diseased tissue, renal oncocytomas disease state and chromophobe renal cell carcinoma disease state), and to also predict clinical outcome (e.g., progressive or non-progressive state of cancer, etc.) of a diseased cell or tissue.